Noise controlled immunoassays

ABSTRACT

A method for reducing false positives and to assay background noise in solid phase immunoassays utilizes a matrix coated on a solid support, which matrix contains an effective amount of a noise reduction component and an effective amount of noise balancing component. Optimization of the matrix composition is obtained by measuring parameters for its effectiveness which include sensitivity ratio, noise balance ratio, and signal to noise ratio.

This invention was made with Government support under Grant No.:SO7RR5441-2 with the National Institutes of Health and the University ofCalifornia. The Government has certain rights in this invention.

TECHNICAL FIELD

The invention relates to immunological testing using solid phaseimmunoassay. More particularly, the invention relates to methods andmaterials to obviate false positives and permit decrease of andquantitation of background noise in such assays.

BACKGROUND ART

Over ten million solid phase immunoassays are run annually in the UnitedStates to detect the presence or absence of specific antibodies orantigens in biological samples, most commonly serum or urine. Falsepositives in tests run in this manner are a common problem, and aresometimes so serious as to create a serious drawback to the use of thetest. For example, recent efforts to screen blood samples for thepresence of AIDS antibodies to certify blood available for transfusionshave resulted in about 70% false positives on the initial screen(Medical World News (August 26, 1985) p. 15; Prentice, R. L. et al,Lancet (3 August 1985) p. 274-275). Furthermore, false positive resultsin screening for antibody to hepatitis B surface antigen threatens toundermine the usefulness of this test to screen patients for the costlyhepatitis B vaccine (Annals of Internal Medicine (1985) 103:791-795).Elimination of false positives can generally be achieved throughfollow-up testing of positive samples using additional controls ordifferent techniques. Although these approaches are expensive and timeconsuming, systematic internal noise control systems to eliminate falsepositives directly at the level of the initial assay have not beengenerally applied.

Some approaches to noise reduction associated with nonspecific bindingof the test sample to the solid substrate in these assays have beenapplied, but these methods do not quantitatively account for thenonspecific binding. For example, Bullock, S. L. et al (J Infect Disease(1977) 136 (suppl): 279-285) disclose the use of albumin to block thesolid substrate after the initial coating layer has been applied;Livesey, J. H. et al., Clin Chim Acta (1982) 123:193-198 and Hashida,S., et al, Clin Chim Acta (1983) 135:163-273 disclose the use of highconcentrations of detergent, salt or protein in the sample buffer. Thesereagents are designed to interfere with nonspecific binding but cannotprevent it completely and cannot quantitate it so as to permit a preciseaccounting for its effect.

The problem of obtaining false positives is of course, aggravated whenthe substance to be detected in a biological fluid is present in quitelow concentrations, thus necessitating the use of sample which is notgreatly diluted. This increases the concentration of potentiallyinterfering materials and thus increases the incidence of falsepositives. It is recognized by the invention herein, though notgenerally in the art, that an analogous circumstance arises in normalmetabolism in situ at least for vertebrate systems, where specificreceptors on target cells must be capable of preferentially bindingtheir specific ligands and rejecting incorrect substances from thesurroundings. Other workers have recognized that specific cell-celladhesion requires a competition between nonspecific repulsion andspecific binding (Bell, G. I., et al, Biophys J (1984) 45:1051-1064). Ithas also been demonstrated that cell surfaces in general bear a netnegative charge (Mehrishi, J. N. in Progress in Biophysics and MolecularBiology (1972), vol 25, Butler, J. A., et al, eds, pp 3-69). It has alsobeen recognized that the anionic surfaces of glomerular basementmembrane and of blood vessel walls are responsible, in part, forinhibiting the transport of large anionic serum molecules across them(Seno, S., et al, Biorheology (1983) 20:653-662; Brenner, B. M., et al,Am J Physiol (1978) 234:5-6).

It has now been found that by mimicking to the appropriate degree (asdetermined by the method of the invention) the surface repulsion of cellsurfaces by the initial layer in solid phase immunoassays, and bybalancing the nonspecific binding or "noise" associated with the initiallayer on a test portion and control surface portion of a solid supportor supports, the specificity of solid phase immunoassay systems can begreatly improved and false positives minimized or eliminated.

DISCLOSURE OF THE INVENTION

The invention provides matrix layers suitable for solid phaseimmunoassays which are inherently superior in eliminating falsepositives to those commonly employed. The invention further providesmeans for verification of the effectiveness of such matrix layers, andfor maximizing their effectiveness, as well as for quantitation ofbackground noise.

In one aspect, the invention is directed to solid phase support having amatrix layer which comprises an effective amount of at least one of acomponent to minimize nonspecific binding (a noise reduction component)and a component to balance nonspecific binding between detecting andcontrol surfaces (noise balancing component). For optimum results, bothnoise balancing and noise reduction components should be present, but itis, of course, possible to obtain the benefits of one without the otherand it may also occur that one material can serve both functions. Inanother aspect, the invention relates to methods for determining theeffective composition of the matrix layer, to detecting targetsubstances in biological fluids using supports coated with this matrixlayer, and to methods of preparing these coated supports.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the relationship between binding of a protein (in thiscase, IgG) to a matrix layer and the isoelectric point of a matrix layerprotein component.

FIG. 2 shows the titration curve of rabbit antiserum raised against thesemen protein p30 using a solid support immunoassay.

FIG. 3 shows the results of a matrix comparison study using an assay foranti-p30 IgG on supports coated with various matrix layer compositions.

FIG. 4 shows the calculated parameters describing the noise reductionand balancing characteristics of various matrix compositions in thetetrads of FIG. 3.

FIGS. 5A and 5B show the results of coating solid supports with matrixlayers comprised of various proteins on sensitivity, noise, andsignal-to-noise ratio.

FIG. 6 shows the results of ELISA determination of anti-p30 IgG in humanserum samples with and without matrix coat noise control.

FIG. 7 shows the results of determination of antibody against BSA invarious human serum samples.

FIG. 8 shows the results of a matrix comparison study to substitute HSAfor BSA as noise balancing component.

FIG. 9 shows the results of a matrix coat noise controlled assay forhuman antibody specific for p30.

MODES OF CARRYING OUT THE INVENTION SOLID SUPPORT IMMUNOASSAYS

In general, solid support immunoassays depend upon coating a supportmaterial, such as a microtiter plate, usually constructed of ahydrophobic material, with an initial layer containing a substanceimmunospecific for the substance to be detected in the sample, and thenin some manner detecting the binding of the material in the testsubstance. Such immunoassays can be run either by detecting the bindingof the target substance, X, itself, or competitively by providinglabelled X which can then compete with whatever amount of X may bepresent in the sample.

In either case, a variety of protocols may be followed. For example, ifX is an antibody, the solid surface is coated with a preparationcontaining an antigen to which the antibody X is specific, the coatedmatrix is treated with sample, and if X is present it will, of course,bind to the specific antigen and be retained. The presence of X on thesolid surface is then determined by a variety of methods, but mostusually by treating the solid with a labelled preparation of an"anti-antibody" specific for the species or class of antibody X, andthen detecting the presence of label. The label may be fluorescent,enzyme, or radioactivity.

On the other hand, if the substance X to be determined is an antigen,the initial layer will contain an antibody or fragment thereof specificagainst X; the presence of X in biological samples can then be detectedusing an additional incubation with labelled antibody or fragment whichbinds to a different antigenic determinant on X than does the antibodyin the initial layer. If the foregoing assays are run competitively, Xitself provides the label, and the X in the sample will simply diminishthe amount of label bound to the solid. The method and materials of theinvention, however, relate primarily to the noncompetitive format or, ingeneral, to "sandwich" assays.

For convenience in discussing the methods and materials of theinvention, certain general terms will be applied to the various layersin typical sandwich assays.

The substance whose presence, absence, or amount in a biological sampleis to be detected will be referred to as the "target" substance. Thetarget substance can be either antigen or antibody.

The substance specific for the target substance which resides in theinitial coating layer on the "solid support" will be referred to as the"surface antitarget". Depending on the nature of the target substance,it will, of course be either an antigen or antibody. The materialapplied to the other side of the sandwich, which contains a means fordetecting the presence of target bound to the solid will be referred toas the "detecting antitarget". While theoretically the detectingantitarget could be an antigen in instances where the target substanceis an antibody, most commonly the detecting antitarget is itself anantibody regardless of the nature of the target. If the target substanceis an antigen, it will be an antibody which binds to a differentantigenic determinant than that of the surface antitarget substance. Ifthe target substance is an antibody, the detecting antitarget isgenerally an immunoglobulin (Ig) raised against the characteristicspecies surface markers associated with the target Ig.

In any event, a positive response in the assay comprises a mutilayercomposite at the surface of the solid support comprising the surfaceantitarget, target substance, and detecting antitarget. It should beunderstood that the detecting antitarget layer can itself comprise amultitude of layers, although this is not generally the case. Forexample, the detecting antitarget might not itself carry the label, butbe bound subsequently to still a fourth layer which does bear such alabel.

Because the method of the invention allows noise to be accounted for ina quantitative fashion, it permits assay of low dilutions of biologicalsample that contain "interferring substances" unrelated to the targetwhich can cause unpredictable noise variations. Such low dilutions arenecessary under circumstances where detection of very low level amountsof materials is desired. This is particularly important where targetsubstances are present in very low concentrations, in particular of theorder of or less than 100 ng per ml of sample.

A number of materials have normal values at very low levels in serum,and employment of the matrix layer in tests for quantitating thesematerials is particularly valuable to control noise due to nonspecificbinding. Exemplary of such materials are ACTH (15-70 pg/ml); calcitonin(0-28 pg/ml); follicle-stimulating hormone, gastrin-1 (0-200 pg/ml);growth hormone (less than 5 ng/ml); insulin (144 pmol/l); luteinizinghormone, parathyroid hormone (less than 25 pg/ml); prolactin (2-15ng/ml); renin (less than 10 ng/ml); immunoglobulin E (less than 700ng/ml). (These estimates of normal values are from the New Eng J Med(1986), 314:39-49). Also, sensitive assays for detection are needed fortumor-specific antigens such as carcinoembryonic antigen and p30. Ofcourse, immunodetection of materials from pathogenic microorganisms mayrequire highly sensitive assays since even minimal numbers of suchorganisms can proliferate and result in disease.

A general problem in control of infectious disease is to diagnoseinfections when the pathogenic organism cannot be isolated. This issolved in one approach by the use of immunoassays to detect risingantibody titers against the pathogens (Basic and Clinic Immunology(1982), Stites, D. P. et al, eds, Lange Medical Publications, Los Altos,Calif., pp 593-636, 672-686). Assays for pathogen-specific antibodywhich could be improved in specificity and reliability using the methodof the invention are those for HTLV/LAV virus (AIDS), hepatitis B virus(serum hepatitis), herpes virus types I and II (herpes encephalitis, andrecurrent herpetic ulcers), toxoplasma gondii (congentialtoxoplasmosis), rubella (congential rubella infection), cytomegalovirus(congenital CMV infection), the various encephalitis viruses, poliovirus, and brucella abortus (brucellosis). Because of the ability of theassays of the invention to be conducted at low dilution, in addition tothe detection of antibodies, the presence of the limited titers of theantigens related to these disease states per se can also be detected.

It should also be noted that the methods of the invention are applicableto sandwich assays conducted with monoclonal as well as polyclonalantibodies. Indeed, they may be particularly applicable to such assays,since immunoglobulins which are used as components of the matrix layeras the surface antitarget have intermediate isoelectric points and areknown to cause nonspecific binding. The increased specificity obtainedin assays using monoclonal antibodies rather than polyclonal sera doesnot alter this nonspecific binding effect which may lead to falsepositive results.

THE PROBLEM OF FALSE POSITIVES

Ordinarily, the solid phase immunoassays to which the invention appliesare conducted by running, in parallel, a "control" portion of the solidsupport which does not contain the surface antitarget, and a "test" or"detecting" portion of the solid support, which does contain the surfaceantitarget. Thus, in the "control surface" portion the bottom layer ofthe sandwich lacks the specific surface antitarget substance. If allworked perfectly, materials which do not contain target would notcontain anything to be bound to the solid support in either the controlsurface or the test region since there is no relevant surface antitargetto hold them. However, to the extent that such binding occurs, it hasbeen assumed that such nonspecific binding could be accurately accountedfor simply by subtracting the amount of label nonspecifically bound inthe control surface portion from that found in the test portion of thesolid support.

As demonstrated herein, this is evidently not true. Even samples whichdo not contain target substance result in differential binding of thedetecting antitarget to the surface antitarget containing (test) andnoncontaining (control surface) portions of the support. This is theessence of a false positive. The problem is aggravated at low dilutionsof biological test sample, because whatever materials are responsiblefor the enhanced nonspecific binding in the presence of a surfaceantitarget are present in larger amounts in these undiluted samples. Thenoise problem is also aggravated when the surface antitarget has anintermediate charge (e.g., an immunoglobulin) or positive charge.

The matrix layer coating of the invention is capable of damping out thisfalse positive reaction and equalizing the nonspecific binding betweenthe detecting and control surface portions of the solid support. Thematrix layer coating may slightly decrease the sensitivity of the test,but effectively eliminates most false positives so that the directsubtracted value (test--control surface) can be used with greaterconfidence in determining the target substance qualitatively orquantitatively. The direct subtracted value can be computed either byobtaining separate results for signal (test surface) and noise (controlsurface) and performing the subtraction, or by automated reference wellsubtraction using analog methods in the circuitry of a detector.

MATERIALS IN THE MATRIX LAYER

Two types of materials are generally required for the most effectivematrix layer. The number of materials actually used to contruct thematrix layer may be more or less, depending on the circumstances of theassay, as will be explained below.

One component (or components) serves to decrease nonspecific binding byproviding a generally repulsive surface mimicking that ordinarily foundon the surface of cells. This component will be referred to as the"noise reduction" component since it reduces nonspecific binding of allkinds, not only that which leads directly to false positives by beingunbalanced in favor of layers containing surface antitarget. In general,the noise reduction component will provide an anionic barrier and willbe, therefore, a negatively charged material, preferably amacromolecule. Certain proteins, for example, are known to be highlynegatively charged at neutral pH; for example, human α-1 acidglycoprotein (AGP), having a pI of 2.7, is an effective choice.

The other component (or components) of the matrix layer of the inventionis designated a "noise balancing" component. This component is selectedfor its ability to balance the nonspecific binding of known negativesamples between the detecting and control surface wells. Bovine serumalbumin (BSA) or human serum albumin (HSA) appear to be effectivechoices for the noise balancing component of the matrix.

Other components may also be included in the matrix of the invention,but the foregoing components are required. It should be noted, however,that the same material may in some cases be effective both as a noisebalancing and noise reduction component; in addition, the noisebalancing component may be a conventional part of the assay, such as theuse of immune and nonimmune serum in assays for a target antigen whereinthe serum components may balance noise.

The proteins suggested above for the noise reduction and noise balancingcomponents of the matrix system are of course merely illustrative, andother proteins, or other macromolecular substances capable of binding tothe usually hydrophobic support either covalently or noncovalently, ormixtures of such materials, could also be used. As a noise reductioncomponent, any negatively charged (at neutral pH) protein, glycoprotein,polyamino acid or other natural or synthetic macromolecule could beused.

Exemplary of the polyamino acids are poly-L-glutamic acid andpoly-L-aspartic acid. Exemplary of other macromolecules are proteinssuch as albumins or α-globulins, glycoproteins such asα-acid-glycoprotein, mucins, fetuin, or red cell glycophorin; exemplarypolysaccharides and proteoglycans include heparin, hyaluronate,chondroitin sulfate, keratan sulfate, and dermatan sulfate; exemplaryglycolipids include gangliosides; and other macromolecules includecross-linked dextran and agarose gels substituted with carboxymethyl orsulfopropyl groups, and detergents with large branching anionichydrophilic head groups. A variety of macromolecules could be designed.In general, their characteristics include a hydrophilic anionic region,a sufficient hydrophobic region to provide nonspecific binding to thesolid support or, in the alternative, to provide linking groups for thepurpose of effecting covalent bonding to the support. Substances ofgreat complexity may not, in fact, usually be necessary for the noisereducing component as is evident from the illustration below. However,they may turn out to be optimal components in some assays for a specifictarget substance. Because only small quantities of the noise reducingcomponents are required and because prospective components can be easilyscreened by the methods described herein, even expensively designedcomponents would not greatly add to the cost of the assay.

With respect to the noise-balancing component, again, any properlydesigned synthetic macromolecule or a variety of naturally occurringmacromolecules could be used. In general, the noise-balancing componentscontain both regions of hydrophobic character and of hydrophiliccharacter, and the steric characteristics should be such that blockageof binding through steric interaction is also possible. Suitableexemplary materials include bovine serum albumin and human serumalbumin, used successfully in the illustration below, serum α-globulinsand α-lipoproteins, as well as synthetic peptides which contain bothhydrophilic and hydrophobic regions. As is the case with the noisereduction component, the amount of material required to provide aneffective matrix layer is sufficiently small that even costly materialscan economically be used.

In instances where the target substance is an antigen, immune andnonimmune sera from the same species may be included in the surfacelayer, and the surface antitarget is then the antibody in the immuneserum. The remaining components of the immune and nonimmune serumconstitute the noise balancing component of the matrix since thesematerials may be close to identical in both control surface and testportions. To complete the matrix layer in this case, only the additionof an anionic charged protein or other macromolecule to provide thenoise reduction component may be needed. On the other hand, in someinstances it may be difficult to obtain non-immune serum which containsthe same collection of interferring substances as does the immune serum.In any event, the method of the invention defines a noise balancingparameter that (HG) may be used to verify this noise-balancing capacityof the non-immune serum.

The solid support to which the matrix is applied may include anyconvenient surface, usually, but not necessarily, hydrophobic, mostcommonly a microtiter plate, but including also plastic tubes, plasticballs, magnetic balls or gels, paper discs, and cellulose-like beads orgels. The binding of the matrix to the substrate can be by a variety oftechniques which include passive adsorption based on hydrophobicbonding, charge binding or other methods of nonchemical binding as wellas covalent linkage of the matrix layer either directly or by use of anintermediary substance coated to the support.

The surface antitarget is most conveniently added to the matrixcomponents prior to coating the initial layer on the support. A two-stepcoating procedure may also be used. For example, the surface antitargetcan first be added to the test portions of the surface, inconcentrations sufficiently low that the surface is only partly coated,followed by coating or binding with matrix layer or the reverse. Indeed,the supports might be supplied already coated with matrix layer and thespecific surface antitarget added according to the specific assay to beemployed. This might require that the surface antitarget to be added bymeans other than simple coating, such as accelerated ion implantation orelectrophoresis.

It should be noted that either noise reduction or noise balancingcomponent can be used alone if desired. In this regard, proteins used inthe art for blocking non-specific binding, such as BSA, are generallyused in concentrations of 5-30 mg/ml--or about 1000 fold the effectiveconcentrations in the matrix layer. As is clear from the results of theassays set forth in Examples 2 and 3 below, use of BSA as a block is noteffective in balancing noise.

METHOD TO OPTIMIZE AND VERIFY MATRIX LAYER COMPOSITION

The invention further offers a method to verify on an ongoing basis theeffectiveness of the particular matrix layer chosen, as well as toselect optimal components for the matrix initially, through ananalytical system designed to maintain assay sensitivity while achievingnoise reduction and noise balance. A straightforward analysis toevaluate various matrix compositions can be used to generate a parameterdesignated a "matrix index", which is defined as the product of asensitivity ratio (SR), a signal to noise ratio, ((S/N)R), and a noisebalance ratio (NBR). While the direct product of these parameters servesas an arbitrary index, as in the explanation below, it may be desirableto weigh, for example, noise balance ratio more heavily than the otherparameters in computing an appropriate matrix index. However, the matrixindex which is calculated as SR×(S/N)R×NBR serves at least as aconvenient screening parameter.

The invention herein includes a particularly preferred and convenientmethod of designing a protocol to determine simultaneously the values ofall three parameters which collectively influence the matrix index.However, a wide variety of experimental designs is possible, and eachparameter could be determined independently. The sensitivity ratio couldbe determined simply by running the assay with and without a particularmatrix layer composition; the noise balance ratio can be determined bycomparing the behavior of samples not containing target in the presenceor absence of surface antitarget, and the signal-to-noise ratio can bedetermined by comparing the binding of samples with and without targetto matrix layers containing surface antitarget. A wide variety ofexperimental designs is possible, and will vary with the number ofcomponents intended to be included in the matrix. The illustration belowis for the typical case, where one component is being tested as a noisereduction component and another as a noise-balancing component. Thisassay design is merely illustrative, and does not limit the scope ofapproaches and experimental protocols which determine fundamentally thesame parameters making up the matrix index.

In this preferred and illustrative embodiment, the values of theparameters which make up the matrix index can be determinedindependently and conveniently by analysis of a series of tetrads whichcontain either no matrix layer or various test matrix formulations. Eachtetrad contains portions with and without surface antitarget and withand without application of a target substance. The tetrads form apattern as shown below:

    ______________________________________                                                               no                                                                      target                                                                              target                                                 ______________________________________                                        surface antitarget A       C                                                  no surface antitarget                                                                            B       D                                                  ______________________________________                                    

Of course, this particular pattern is arbitrary and any configurationwhich contains these elements may be used. In the discussion below,"wells" is used to refer to any defined portion of the support surface.Such portions can be defined, for example, as fractions of collectionsof beads or particles, areas in a column, or, in the conveniently usedmicrotiter plates, actually as wells.

Referring to the configuration shown above, wells A and C containsurface antitarget; wells B and D do not. Wells A and B will be suppliedtarget substance, wells C and D will not.

It will be recognized that the pairs of wells (A and B) and (C and D)each comprise the usual test and control surface wells as such assaysare ordinarily conducted. Wells C and D will also serve to illustratethat in the absence of matrix layer, or in the presence ofinappropriately constructed matrix, nonspecific binding of detectingantitarget for samples containing no target substance may bedifferential in the presence or absence of surface antitarget. Bycomparing a series of tetrads with various matrices, those matriceswhich produce identical readings in wells C and D clearly balance thenoise due to nonspecific binding; those which produce least response inC as compared to A reduce the noise level relative to signal the best,and those which provide the highest corrected reading for A (after B issubtracted) show the greatest sensitivity.

In this particular protocol, the noise balance ratio, NBR, is defined asthe ratio of the signals in C and D, with the smaller of the two valuesplaced in the numerator. NBR is thus C/D or D/C.

In this protocol, the signal to noise ratio, (S/N)R, is defined as thecorrected signal (A-B) divided by C. The noise is the apparent signalproduced in the presence of surface antitarget but in the absence oftarget in the sample. C is used rather than B in the denominatorbecause, in order to evaluate noise, higher concentrations of nontargetsubstances in the sample (e.g., as found in serum or other biologicaltest samples) often are used in C and D than are provided in A and B. Inother words, a relatively high sample dilution (containing target) maybe used for A and B but a relatively low one (without target) for C andD.

In this protocol, the sensitivity ratio, SR, is not a parameterassociated with each tetrad per se but rather the ratio of the correctedsignal in a test tetrad as compared to that in a tetrad containing nomatrix. This provides a measure of the loss of sensitivity due to thepresence of the matrix layer. SR represents the ratio of the differenceA-B in the matrix coated tetrad divided by the difference A-B for thetetrad not coated with matrix.

In order properly to evaluate these parameters, the surface antitarget,target substance, and matrix providing materials should be provided atdilutions or concentrations in accordance with certain optimizationconsiderations. In general, for immunoassays which employ passiveadsorption to polystyrene microtiter wells, for example, the surfaceantitarget should be applied at a concentration of less than 10 μg/ml ashigher concentrations may lead to decreases in assay sensitivity due tothe "hook" effect. In fact, concentrations less than 1 μg/ml areconvenient. The target substance is supplied at a concentration which isin the linear region of its titration curve against the selectedconcentration of surface antitarget. The linear region may be determinedby titrating serial dilutions of biological sample containing targetsubstance against the surface antitarget. The linear region is selectedbecause interference caused by the matrix layer to surface antitargetbinding to target will be detected immediately by a linear loss of assaysensitivity. The dilution of a corresponding background sample ofbiological fluid containing no target is optimally a low dilution (about1:1-1:9, v/v) in order to enhance the noise level for evaluation. Atitration curve for the background fluid against the selectedconcentration of surface antitarget may also be determined.

Matrices of various compositions are tested using a series of testtetrads. Each tetrad represents a unique formulation of matrixcomponents. Each tetrad is evaluated internally for noise reduction andbalance, and relative to a tetrad containing no matrix for sensitivity.An arbitrarily determined product of these factors, the matrix index,then gives a measure of the effectiveness of the matrix layer for eachtetrad in optimizing the assay. The matrix layer composition having anoise balance ratio close to unity and the highest matrix index, or, ifdesired, an alternatively weighted product of the above parameters, ischosen.

The validity of the noise-balancing aspect of the matrix layercomposition is verified during the conduct of a typical assay. In atypical assay, one or more negative samples having intermediate to highbackground noise levels can be tested in both the detecting and controlwells. The binding of these samples should be essentially equal in bothwells, yielding a noise-corrected signal close or equal to zero. Thisconfirms that the noise balance feature is properly adjusted for thatday's run. Standard positive controls will also be run each day toconfirm that the surface antitarget-containing detecting wells are alsoproperly adjusted.

If desired, samples identified as positive during testing may beverified by a competition assay. An appropriate dilution of the positivesample (sufficiently diluted to yield a weak but statisticallysignificant positive) can be preincubated with a soluble form of thesurface antitarget substance (generally in a concentration range ≦25-50times the concentration of antitarget used to coat the test surface).This preincubation with soluble antitarget will competitively inhibitbinding of the target to the test surface. Hence, binding of thesepreincubated samples should be essentially equal in both detecting andcontrol wells, again yielding a noise-corrected signal close or equal tozero. Thus, the ability of the matrix layer to balance nonspecificbinding (noise) between the detecting and control wells, and its abilityeffectively to eliminate most false positives can be verified on anongoing basis by including proper negative and (if desired) positivecontrols for each assay run.

EXAMPLE

The following examples are intended to illustrate but not to limit theinvention.

PREPARATION A Preliminary Screening of Coating Components

Initial selection of suitable matrix components which reduce noise byinhibiting nonspecific binding of rabbit IgG and of rabbit nonimmuneserum was determined by comparison to test surfaces coated withpoly-L-arginine, a positively charged polymer.

Immulon II Removawells (Dynatech Laboratories, Alexandria, VA) werecoated overnight at 4° C. with 10 μg/ml of the components to be testedin coating buffer (0.1 M sodium bicarbonate, pH 9.8) (0.35 ml/well), thewells were washed and detergent blocked with 0.4 ml/well of phosphatebuffered saline containing 0.05% Tween-20 ("PBS-T", which is 0.15 MNaCl, 0.01 M phosphate, pH 7.4, 0.05% Tween-20).

The wells were incubated at room temperature for 90 minutes with 0.35ml/well antigen buffer (PBS-T with 10 mM EDTA) containing either 0.5mg/ml pooled rabbit IgG or a 1:4 (v/v) dilution of reconstituted pooledrabbit serum (both nonimmune, hence representing sample backgroundnoise). After washing with PBS-T, the bound serum immunoglobulins orantibodies were detected by incubating for one hour at room temperaturewith goat anti-rabbit IgG labelled with alkaline phosphatase (SigmaChemical Co., St Louis, MO) at 1:1499 (v/v) dilution in PBS-T, followedby treating with 4 mM p-nitrophenyl phosphate in substrate buffer (10%diethanolamine, 0.01% magnesium chloride, 0.02% sodium azide, pH 9.8)for 30 minutes at 37° C. The enzymatic reaction was stopped with 50 μlof 4 M sodium hydroxide and the absorbance was read at 410 nm on aMICROELISA minireader (Dynatech Laboratories, Alexandria, VA).

In all cases a % maximum absorbance was obtained using thepoly-L-arginine coat set arbitrarily at 100% maximum. The seriesconsisted of proteins, glycoproteins, and synthetic polypeptides ofdiffering isoelectric points. A progressively increasing percentage ofthe maximum absorbance was observed, in direct correlation with theincreasing isoelectric points of the proteins. The correlation wassubstantially linear, as shown in FIG. 1.

In FIG. 1, the precent maximum absorbance for binding of IgG from pooledrabbit IgG and rabbit serum as measured by ELISA is plotted against theisoelectric point of each coating peptide. The average absorbance forbinding of rabbit IgG from the pooled IgG (A₄₁₀ =1.76) and pooled serum(A₄₁₀ =1.23) to the poly-L-arginine coat by ELISA was set as 100% ofmaximum absorbance respectively. The % maximum absorbance for (IgGbinding to) protein X (in the test well coat) is thus calculatedrelative to these values. Separate regression lines for % maximumabsorbance representing binding of IgG from pooled rabbit IgG and pooledrabbit serum were calculated by least squares. Each point is the averageof duplicate determinations in a single experiment.

The isoelectric point of the coating peptides and glycopeptides are asfollows:

    ______________________________________                                        Poly-L-glutamic acid 1.8                                                      Poly-L-aspartic acid 2.3                                                      α.sub.1 -acid glycoprotein,                                                                  2.7                                                      human.sup.1                                                                   Albumin, bovine serum.sup.2                                                                        4.7                                                      Albumin, human serum.sup.1                                                                         4.9                                                      Transferrin, human.sup.1                                                                           5.2                                                      Hemoglobin, human.sup.3                                                                            6.9                                                      Myoglobin, equine.sup.4                                                                            7.3                                                      Lactoferrin, human breast                                                                          8.7                                                      milk.sup.1                                                                    Cytochrome c, equine heart.sup.1                                                                   10.6                                                     Poly-L-arginine      14.0                                                     ______________________________________                                    

Estimated isoelectric points for the synthetic polypeptides werecalculated from the Henderson-Hasselbach equation using approximatepI_(a) values of the ionizable side chain groups. The number of aminoacid residues were calculated from the estimated molecular weights:poly-L-glutamic acid (M_(r) =60,000); poly-L-aspartic acid (M_(r)=20,000); and poly-L-arginine (M_(r) =100,000). By Henderson-Hasselbachanalysis, poly-L-arginine would still have an overall positive charge asthe pH approached 14. Hence, this theoretical pH was designated as itsisoelectric point for purposes of this analysis. The isoelectric pointfor lactoferrin represents an average for the reported range of 8.2-9.2.

The remaining pI values were obtained from the literature as follows:

1. Fasman, G.D., ed, Handbook of Biochemistry and Molecular Biology(1975), vol II, CRC Press, Cleveland, OH.

2. Malamud, D., et al, Anal Biochem (1978) 86:620-624.

3. Righetti, P.G., et al, J Chromatog (1976), 127:1-28.

4. BDH Chemicals Ltd. Isoelectric Point Markers, Product Information, pp1-5, Poole, England.

This suggests that the nonspecific binding of IgG alone or in serum to ahydrophilic protein-coated surface is primarily a function of thesurface charge imparted by the coating protein. Nonspecific hydrophobicbinding in these assay systems is inhibited by inclusion of detergentsin the test sample buffers. From these results one would also expectthat those substances with the lowest percentage of maximum absorbance(i.e., those with the lowest isoelectric points) would be substancesmost likely to serve as effective noise reduction components in amatrix.

To further test the ability of proteins of differing isoelectric pointsto decrease assay noise, several of the proteins tested in the foregoingprotocol were coated at various concentrations to test their effects onthe signal to noise ratio in an ELISA conducted generally as describedin Example 1 below. The results of this assay are shown in FIG. 5A; allproteins consistently decreased the signal, but proteins having a netnegative charge also decreased noise at low concentration. As shown inFIG. 5B, the signal to noise ratio improves initially with small amountsof all negatively charged proteins, and maintains an improvement to ahigh concentration for AGP (the most negatively charged). Thus, AGPappears to be the best candidate in this series of test substances foruse as the noise-reducing component in a matrix. Desialization of theAGP using standard procedures depletes it of negative charge andsignificantly diminishes its ability to maintain a high signal to noiseratio.

EXAMPLE 1 Optimization of Matrix Coat

An optimized matrix was determined for a particular application in theassay of biological samples for anti-p30 antibody. The antigen p30 is a30kd glycoprotein which is found in human semen and appears to begenerated only in males. An assay for the antigen using a sandwichapproach on solid supports without the matrices of the invention, wasdisclosed in Graves, H.C.B. et al. New England Journal of Medicine(1985) 312:338-343.

Because p30 appeared to be male-specific, it was reasoned that somesexually active women might become sensitized to this foreign substanceand make antibodies to it. Such antibodies, if found, could contributeto problems with fertility or vaginitis in these women. To investigatethis possibility, an optimized matrix coat for assay noise control wasdesigned for an immunoassay to detect low levels of anti-p30 antibody.In the determination herein, the target substance is anti-p30 IgG inrabbit serum, the surface antitarget is p30 protein (purified asdescribed by Sensabaugh, G.F. J Forensic Science (1978) 23:106-115), andthe detecting antitarget is alkaline phosphatase-labeled goat antibodiesspecific for rabbit IgG.

To design an optimized matrix coat, Immulon II™ flat bottom Removawells(Dynatech Laboratories, Alexandria, VA) were divided into tetrads of thegeneral pattern described hereinabove, each tetrad containing two testand two blank control wells. The blank control wells, B and D of eachtetrad, were coated with test matrices containing various concentrations(0-10 μg/ml) of the noise reduction component, human alpha-1 acidglycoprotein (AGP) and various concentrations (0-8 μg/ml) of the noisebalancing component, bovine serum albumin (BSA), RIA grade. (Bothsubstance were provided by Sigma Chemical Co., St. Louis, Mo.) The testwells, A and C of each tetrad were coated with the correspondingmatrices containing 1 μg/ml of purified p30 antigen (surfaceantitarget). Coating was carried out in "coating buffer" (0.1 Mbicarbonate, pH 9.8) at 4° overnight.

The coated plates with the tetrads containing blank control and testwells were washed three times, 0.40 ml/well, with PBS-T (see PreparationA). The plates were then blocked using 0.4 ml/well PBS-T for 1 hour atroom temperature.

The coated, washed, blocked, plates were then used to assay for thepresence or absence of target substance, rabbit antibody to p30, byincubating wells A and B of each tetrad with a 1:999 (v/v) dilution ofpooled polyclonal antiserum (raised in rabbits against purified p30antigen) in antigen buffer (0.05 M HEPES, pH 7.4, 0.4 M NaCl, 10mM EDTA,0.05% Tween-20) for 11/2 hours, at 0.35 ml/well, at room temperature.(This dilution had been determined by titrating the rabbit antiserumusing wells coated as above, without matrix components, but with 1μg/mlpurified p30 antigen, and detecting the bound antisera using alkalinephosphatase labelled goat anti-rabbit IgG as described below. Theresults of this titration, shown in FIG. 2, indicate that a 1:999 (v/v)dilution is in the linear portion of the curve.

Wells C and D of each tetrad were correspondingly incubated with a 1:4(v/v) dilution in antigen buffer of nonimmune serum obtained fromrabbits of the same species which had not been subjected to immunizationwith p30.

The plates were again washed four times with 0.4 ml/well PBS-T and thebound antibody was detected by incubating all wells for one hour at roomtemperature with 0.35 ml/well of a 1:1499 (v/v) dilution of detectingantitarget, goat anti-rabbit IgG labelled with alkaline phosphatase(Sigma Chemical Co., St. Louis, MO).

The plates were then washed three times with 0.40 ml/well PBS-T andincubated at 37° C. with 0.25 ml/well of substrate solution containing 4mM p-nitrophenyl phosphate in substrate buffer (10% diethanolamine,0.01% magnesium chloride, 0.02% sodium azide, pH 9.8). The enzymereactions were stopped with 4 M NAOH, 0.05 ml/well, after 30 minutes,and the absorbance of each well read at 410 nm on a MICROELISA reader(Dynatech Labs, Alexandria, VA).

The results, given in corrected absorbance units at 410 nm, for a plateof 9 tetrads is shown in FIG. 3. Blank control wells which were treatedwith nonimmune serum diluted 1:4 (v/v) but not with detecting antitargetwere arbitrarily set at 0 to obtain a corrected reading for wells A, B,C, and D.

Using the formulas set forth above, a sensitivity ratio, signal to noiseratio, and noise balance ratio were calculated for each tetradrepresenting a different matrix formulation, and a matrix index for eachobtained. The wells are designated by their horizontal (matrixconcentration of BSA) and vertical coordinates (matrix concentration ofAGP) in FIG. 3.

Of course, the SR for well 0.0 is 1 by definition; the SR for well 0.5is 1.72/2.0 or 0.86; that for well 0.10 is 1.69/2.0 or 0.85, and soforth.

The (S/N)R for each well is calculated independently as (A-B)/C (i.e.the reading obtained for A minus B (zero in this case) divided by thesignal for C which represents the noise due to nonspecific binding ofnonimmune serum at low dilution). Thus, for well 0.0 (S/N)R is 2.0/0.39or 5.1; for well 0.5 (S/N)R is 1.72/0.23 or 7.5; for well 0.10 it is1.69/0.17 or 9.9, and so forth.

This series of wells represents increasing concentrations of noisereduction component in the matrix. It is clear that the signal to noiseratio is desirably affected. Corresponding values of the signal to noiseratios for wells 4.0 and 8.0, which contain increasing concentrations ofnoise balancing component of the matrix are 6.2 and 4.9 respectively. Itis apparent that this component is not very helpful with respect tosignal to noise ratio reduction, and has an undesired effect atconcentrations of 8 μg/ml or greater.

The noise balance ratio (NBR) is calculated as the ratio of C/D or thereciprocal, depending on which is greater, and is ideally one, wherenoise is perfectly balanced. For proper assay noise control, it isessential that the NBR be as close to one as possible, as this allowsone to measure the "noise" of the test sample in the blank control welland subtract it from the test well signal. In the control tetrad 0.0 theNBR is 0.39/0.16 or 0.41; for increasing amounts of the noise reductioncomponent this ratio improves but does not approach one; in tetrad 0.5,the NBR is 0.48; in tetrad 0.10 it is 0.71. However, marked improvementis found as increasing amounts of the noise balancing BSA component areadded. In tetrad 4.0 the NBR is 0.92; in tetrad 8.0, it is 0.68,indicating that an excess of this component has overbalanced the noise.

FIG. 4 shows a summary for the results for all 9 tetrads; listed inorder are SR, (S/N)R, NBR, and finally, MI (the matrix index).

FIG. 4 shows that the optimum matrix composition in this series isrepresented by tetrad 4.10. This matrix seems to achieve the properbalance of noise reduction component and noise balancing component. Thesensitivity of the assay is diminished only slightly; indeed roughly thesame order of diminution in sensitivity is found in all tetradscontaining matrix. The higher matrix index for tetrad 4.10 than for 4.0appears to be due mainly to an enhancement of the signal to noise ratio,as well as some improvement in balance, as would be expected from theincreased concentration of the noise reduction component (AGP) of thematrix. Note that the lowest matrix index (i.e., the tetrad with thepoorest noise control) was obtained for tetrad 0.0 which contained nomatrix coat. This is the standard configuration for current solid phaseimmunoassays.

EXAMPLE 2 The Use of the Matrix in Noise Detection Elimination of FalsePositives

Comparative analyses with and without the matrix coating on the solidsupport were conducted using anti-p30 rabbit serum, nonimmune rabbitserum, purified nonimmune rabbit IgG and poly-L-lysine, a prototype fora cationic cross-reacting substance. The assays were conducted preciselyas set forth in Example 1, but with the blocking step either conductedas above with (PBS-T) or with a PBS-T containing 1% BSA (wt/v). Thematrix coat is 10 μg/ml AGP+4 μg/ml BSA and the surface anti-target inthe test wells is p30 at 1 μg/ml. The matrix thus corresponds to tetrad4.10 of Example 1. The results are shown in Table 1 below.

                  TABLE 1                                                         ______________________________________                                                     *IS  NS     NS     IgG 1 poly-L                                               1:999                                                                              1:4    1:1    mg/ml 10 μg/ml                             ______________________________________                                        No matrix                                                                              Test      1.50   .32  .53  .49   1.07                                (Block:  Ctrl Sfc  .00    .23  .36  .14   .22                                 PBS-T)   Corrected 1.50   .09  .17  .35   .85                                 No matrix                                                                              Test      1.87   .60  .86  .74   1.16                                (Block:  Ctrl Sfc  .00    .18  .35  .12   .54                                 BSA 1% in                                                                              Corrected 1.87   .42  .51  .62   .62                                 PBS-T)                                                                        Matrix Coat                                                                            Test      1.29   .20  .27  .32   1.51                                (Block;  Ctrl Sfc  .00    .20  .29  .28   1.66                                PBS-T)   Corrected 1.29   0    -.02 .04   -.15                                ______________________________________                                         *IS = rabbit antiserum pooled from rabbits immunized against p30;             NS = pooled rabbit nonimmune serum;                                           IgG = purified nonimmune rabbit IgG from a different pool;                    poly-L = polyL-lysine.                                                   

The results are clear that whether blocking was conducted with Tween(PBS-T) alone or Tween plus BSA, all known negatives gave false positiveresults. This was true even though the control surface well reading wassubtracted from the test well reading. However, when the matrix coat wasused, neither the nonimmune serum nor IgG controls gave noticeablepositive readings; the result for poly-L-lysine was greatly improved,though less than perfectly balanced. Cationic poly-L-lysine iselectrostatically attracted to the negatively charged matrix.

EXAMPLE 3 Assay of Human Serum for anti-p30 with Matrix Coat Control

The method of Example 2 was applied generally as there described exceptthat the detecting antibody was alkaline phosphatase labelled goatanti-human IgG F(ab')₂ specific for the gamma chain of human IgG (SigmaChemical Company, St. Louis, MO).

Human sera from 19 men and women were tested with and without matrixcoat control, wherein the matrix coat is obtained by incubating theImmulon II™ Removawells in 10 μg/ml human AGP and 4 μg/ml BSA in coatingbuffer; for the the detecting wells the matrix composition is inadmixture with 1 μg/ml p30. For the standard ELISA (used here forcomparison), p30 at 1 μg/ml in coating buffer was used for the detectingwells, and coating buffer alone for the blank control wells.

After coating overnight at 4° C., the support was washed as above andblocked either with PBS-T or PBS-T with 1% BSA, by incubating for onehour at room temperature. The supports were again washed as above, priorto the application of sample. Human sera were supplied as a 1:2 dilution(v/v) in BSA-antigen buffer (0.05 M HEPES, pH 7.4, 0.6 M NaCl, 15 mMEDTA, 0.75% v/v Tween-20, 1.5% wt/v RIA grade BSA), after a one-halfhour incubation in test tubes. Incubation in the wells was for 1.5 hoursat room temperature. The supports were again washed, and bound targetdetected as described in Example 2, but with the above-mentionedappropriate detecting antitarget. The results are shown in Table 2 andare plotted in FIG. 6.

                                      TABLE 2                                     __________________________________________________________________________    ELISA to Detect Human IgG Antibody Specific for p30: Comparison of            Matrix                                                                        Coat Control with Tween-20 and BSA-Tween-20 Coat Control                      Subject   A B  C D E  F  G  H  I  J K  L  M  N  O  P  Q  R  S                 __________________________________________________________________________    ELISA with Matrix Coat Control                                                Detecting Well                                                                          .12                                                                             .27                                                                              .16                                                                             .22                                                                             .15                                                                              .55                                                                              .53                                                                              .39                                                                              .42                                                                              .33                                                                             .15                                                                              .19                                                                              .38                                                                              .14                                                                              .10                                                                              .19                                                                              .22                                                                              .18                                                                              .23               Control Well                                                                            .08                                                                             .25                                                                              .13                                                                             .21                                                                             .15                                                                              .12                                                                              .19                                                                              .42                                                                              .42                                                                              .26                                                                             .11                                                                              .19                                                                              .35                                                                              .11                                                                              .11                                                                              .20                                                                              .23                                                                              .22 .25              Corrected Signal                                                                        .04                                                                             .02                                                                              .03                                                                             .01                                                                             0  .43                                                                              .34                                                                              -.03                                                                             0  .07                                                                             .04                                                                              0  .03                                                                              .03                                                                              -.01                                                                             -.01                                                                             -.01                                                                             -.04                                                                          -.02                 ELISA with Tween (0.05%) Block                                                Detecting Well                                                                          .35                                                                             .39                                                                              .55                                                                             .60                                                                             .35                                                                              1.00                                                                             1.60                                                                             .80                                                                              .74                                                                              .62                                                                             1.10                                                                             .51                                                                              .55                                                                              .65                                                                              .35                                                                              .65                                                                              .56                                                                              .53                                                                              .92               Control Well                                                                            .31                                                                             .54                                                                              .36                                                                             .50                                                                             .36                                                                              .39                                                                              .55                                                                              .89                                                                              .83                                                                              .53                                                                             .44                                                                              .45                                                                              .67                                                                              .36                                                                              .44                                                                              .72                                                                              .79                                                                              .69 .59              Corrected Signal                                                                        .04                                                                             -.15                                                                             .19                                                                             .10                                                                             -.01                                                                             .61                                                                              1.05                                                                             -.09                                                                             -.09                                                                             .09                                                                             .66                                                                              .06                                                                              -.12                                                                             .29                                                                              -.09                                                                             -.07                                                                             -.23                                                                             -.16                                                                          .33                  ELISA with BSA (1%) and TWEEN (0.05%) Block                                   Detecting Well                                                                          .40                                                                             .61                                                                              .48                                                                             .60                                                                             .36                                                                              1.19                                                                             1.75                                                                             1.00                                                                             .85                                                                              .81                                                                             1.00                                                                             .49                                                                              .59                                                                              .70                                                                              .35                                                                              .60                                                                              .51                                                                              .48                                                                              .95               Control Well                                                                            .32                                                                             .59                                                                              .30                                                                             .53                                                                             .32                                                                              .37                                                                              .67                                                                              1.08                                                                             .90                                                                              .70                                                                             .45                                                                              .45                                                                              .66                                                                              .32                                                                              .47                                                                              .77                                                                              .74                                                                              .63 .43              Corrected Signal                                                                        .08                                                                             .02                                                                              .18                                                                             .07                                                                             .04                                                                              .82                                                                              1.08                                                                             -.08                                                                             -.05                                                                             .11                                                                             .55                                                                              .04                                                                              -.07                                                                             .38                                                                              -.12                                                                             -.17                                                                             -.23                                                                             -.15                                                                          .52                  __________________________________________________________________________

It is apparent from the examination of FIG. 6 that matrix coatcontrolled assay samples showed clear positive or negative results,whereas the assays run in the absence of matrix gave a considerablespread, which depending upon its interpertation, includes falsepositives. In particular, subjects K, N, and S had elevated signallevels using ELISA without matrix control, although matrix coat controlshowed them to be negative for anti-p30. Samples F and G, which werepositive in the matrix controlled assay, were shown to actually containanti-p30. By preincubating 1:4 (v/v) dilutions of these samples with 50μg/ml of purified p30, signals in these samples dropped to nonimmunebackground levels, i.e., approximately zero.

Also of importance, these results demonstrate that the "noise level"measured for each individual test sample was unique to that sample. Todetermine the magnitude of target-specific signal present in a sample,one must be able to measure the amount of noise present in the sample.This must be done in a noise-balanced assay, i.e., the subtracted noisecannot be altered by the presence or absence of antitarget on thecontrol surface. For example, subjects H, J, and M had relatively highsignal levels in the detecting wells containing the matrix coat withp30, but they also had essentially identical signal levels in the blankcontrol wells which contained only the matrix coat. This indicates thatthe detecting well signal was not specific for the antitarget (i.e.,p30).

Because the noise level in general is unique to each sample (asdemonstrated here), correct assay results depend upon the ability tomeasure this noise accurately so that it can be subtracted from thedetecting well signal. Because the control surface well is made anaccurate measure of noise by the method of the invention, thissubtraction becomes feasible, thereby providing a valid measure ofsignal. Also note that matrix coat noise control tightly clustersnegative sample values around zero (i.e, decreases variance) a featurethat dramatically simplifies the statistical calculations necessary fordata analysis.

EXAMPLE 4 Detection of Anti-BSA in Humans

Nine of 10 samples of human sera tested as described below, using amatrix coat control wherein HSA was substituted for the surfaceantitarget BSA in the control wells, showed the presence of antibodiesto BSA. The presence of this antibody in the population may account fora measurable portion of nonspecific binding in solid phase assays run onhuman samples if BSA is used in a blocking step of the assay. Therefore,as this assay demonstrates, false positives may also be minimized bypretreating the samples to be tested with an effective amount of BSA inthe antigen buffer.

For this assay, both control and test wells were incubated with 1 μg/mlhuman serum albumin (HSA) in 10/μg/ml AGP in counterbalance to the testwells which were incubated with 1 μg/ml bovine serum albumin (BSA) in10/μg/ml AGP. Since HSA and BSA have essentially the same isoelectricpoint, it was surmised that HSA used in the same concentration in thecontrol well as BSA (in the test well) would effectively serve as thenoise balancing component. This was confirmed by demonstrating that testwells and their corresponding control wells had a noise balance ratio ofunity when tested with a 1:2 (v/v) of nonimmune human sera (sera whichhad been preabsorbed for 30 minutes with 0.5% BSA, wt/v, at 37° C.).

For conduct of the assay, the procedure was generally as set forthabove. Human sera were diluted 1:2 (v/v) in antigen buffer (see above)and preincubated in duplicate for 30 minutes at 37° C. with and withoutthe addition of 0.75% BSA (wt/v) to the buffer.

Duplicate samples of normal serum were incubated for 1.5 hours at roomtemperature in test and control wells. The same samples absorbed withBSA were similarly incubated in the test wells. The general protocol:matrix coat, wash, block (PBS-T), wash, sample incubation, wash,detection with alkaline phosphatase labeled goat anti-human IgGfragments was as described in Example 3 above.

Nine of the ten sera demonstrated significant levels of anti-BSA IgG asshown in section 1 of Table 3; however, incubation of the sera withBSA-containing buffer resulted in removal of the IgG and a cluster ofnull results (section 2 of Table 3). FIG. 7 shows a graphicrepresentation of these results.

                                      TABLE 3                                     __________________________________________________________________________    Detection of Anti-BSA IgG in Human Serum by Matrix Coat Noise-controlled      ELISA                                                                         Subject  1   2   3   4   5   6   7   8   9   10                               __________________________________________________________________________    ELISA for Anti-BSA IgG                                                        Detecting Wells                                                                        1.305                                                                             1.43                                                                              1.72                                                                              1.325                                                                             1.345                                                                             1.165                                                                             1.54                                                                              1.05                                                                              0.47                                                                              0.82                             Control Wells                                                                          0.22                                                                              0.265                                                                             0.30                                                                              0.175                                                                             0.145                                                                             0.20                                                                              0.28                                                                              0.215                                                                             0.415                                                                             0.135                            Corrected Signal                                                                       1.085                                                                             1.165                                                                             1.42                                                                              1.15                                                                              1.20                                                                              0.965                                                                             1.26                                                                              0.835                                                                             0.055                                                                             0.685                            ELISA for Anti-BSA IgG (Sera in detecting wells preincubated with 0.5%        BSA)                                                                          Detecting Wells                                                                        0.245                                                                             0.235                                                                             0.335                                                                             0.14                                                                              0.14                                                                              0.17                                                                              0.27                                                                              0.215                                                                             0.41                                                                              0.135                            Control Wells                                                                          0.22                                                                              0.265                                                                             0.30                                                                              0.175                                                                             0.145                                                                             0.20                                                                              0.28                                                                              0.215                                                                             0.415                                                                             0.135                            Corrected Signal                                                                       0.025                                                                             -0.03                                                                             0.035                                                                             -0.035                                                                            -0.005                                                                            -0.03                                                                             -0.01                                                                             0.00                                                                              -0.005                                                                            0.00                             __________________________________________________________________________     All values represent absorbance units at 410 nm.                         

These results show that anti-BSA antibody present in low concentrationsin most human sera may contribute to false positive results inimmunoassays which use BSA in a blocking step. These sera must thereforebe preabsorbed with an excess of BSA to competitively inhibit binding ofthis antibody. As demonstrated here, these low levels of anti-BSAantibody in human sera can be measured by an immunoassay with matrixcoat noise control.

EXAMPLE 5 Development of an Alternative Matrix Composition

Because humans may exhibit antibodies to a wide variety of animalproteins due to dietary exposure (e.g., BSA, casein from cow's milk,gelatin, etc.), it may be desirable to eliminate nonhuman animalproteins from matrices in immunoassays which detect human antibodies tovarious antigens.

Therefore the procedure described above, and illustrated in Example 1,was used to determine a substitute matrix incorporating AGP and HSA foruse in the detection of anti-p30 IgG in humans. As the optimum AGPconcentration had already been determined (i.e., 10 μg/ml), it wasnecessary only to analyze tetrads with variable amounts of HSA.

Tetrads were organized as described in Example 1 containing 10 μg/ml ofnondenatured human serum albumin (Calbiochem, San Diego, CA). Rabbitanti-p30 serum, diluted 1:999 (v/v) in antigen buffer containing 0.5%(wt/v) BSA was used as the positive control (containing target);nonimmune rabbit sera diluted 1:2 (v/v) to yield the same bufferconcentration was used as negative control (containing no target). Theprotocol was as described above, using PBS-T blocking, and the dilutedsamples were incubated in the test and control wells for 1.5 hours atroom temperature. The results are shown in FIG. 8.

The matrix composition containing 6 μg/ml HSA in addition to the 10μg/ml of AGP appeared to be most favorable; this tetrad also had thenoise balance ratio closest to unity (0.98).

EXAMPLE 6 Application of the HSA-Containing Matrix

The matrix composition shown to be optimum in Example 5 was used inperforming the assay for anti-p30 in the serum of 18 women, using 1:3(v/v) dilution of serum from subject F of Example 3 as a positivecontrol. The procedure was exactly as described in Example 3, except forthe nature of the matrix.

The results are shown in Table 4 and plotted in FIG. 8. The positivecontrol and one subject (105) showed the presence of antibody; theremaining subjects gave a cluster of null results. The levels detectableare less than 5 ng/ml. Again note the highly variable noise levels inthese minimally diluted sera which often exceed the signal levels in thepositive sera (see subjects 106, 107, and 128 in Table 4). Matrix coatnoise control demonstrates the elevated signal levels in these sera tobe due to background noise factors not related to the presence of target(anti-p30 IgG) in the samples.

                                      TABLE 4                                     __________________________________________________________________________    An ELISA to Detect Human IgG Antibody Specific for p30:                       Results with a Matrix Coat Control Composed of Human Proteins Only            ELISA with Matrix Coat Control                                                __________________________________________________________________________    Subject  101 102 105 106 107 108 109 111 112 113                              __________________________________________________________________________    Detecting Well                                                                         .365                                                                              .285                                                                              .565                                                                              .445                                                                              .59 .375                                                                              .155                                                                              .135                                                                              .315                                                                              .325                             Control Well                                                                           .265                                                                              .35 .36 .515                                                                              .695                                                                              .315                                                                              .195                                                                              .175                                                                              .24 .33                              Corrected Signal                                                                       .10 -.065                                                                             .205                                                                              -.07                                                                              -.105                                                                             .06 -.04                                                                              -.04                                                                              .075                                                                              -.005                            __________________________________________________________________________    Subject  114 115 116 118 119 126 128 129 +                                    __________________________________________________________________________    Detecting Well                                                                         .43 .305                                                                              .265                                                                              .22 .145                                                                              .22 .48 .255                                                                              .455                                 Control Well                                                                           .56 .325                                                                              .33 .225                                                                              .18 .21 .495                                                                              .28 .285                                 Corrected Signal                                                                       -.13                                                                              -.02                                                                              -.065                                                                             -.005                                                                             -.035                                                                             .01 -.015                                                                             -.025                                                                             .17                                  __________________________________________________________________________     All values represent average absorbance units at 410 nm.                 

I claim:
 1. A solid support for the conduct of immunoassay protocols atthe surface of said support, wherein said support is coated with amatrix layer,which matrix layer comprises an effective amount of both anoise reduction and a noise balancing component, wherein said noisereduction and noise balancing components are different from each otherand different from any surface anti-target used in the immunoassay. 2.The support of claim 1 wherein the noise reduction component is amacromolecule having a pI below 6 and the noise balancing component is amacromolecule having a pI higher than that of said noise reductioncomponent.
 3. The support of claim 1 wherein the noise reductioncomponent is selected from the group consisting of a polyamino acid,protein, glycoprotein, polysaccharide, glycolipid, and amphipathicmacromolecules and wherein the noise-balancing component is selectedfrom the group consisting of proteins, polypeptides, and amphiphaticmacromolecules.
 4. The support of claim 3 wherein the noise reductioncomponent is α-acid glycoprotein (AGP) and the noise balancing componentis selected from the group consisting of human and bovine serum albumin(HSA and BSA).
 5. The support of claim 1 wherein the matrix layer isobtained by a process which comprises incubating the support with asolution containing about 4 μg/ml BSA.
 6. The support of claim 4 whereinthe matrix layer is obtained by a process which comprises incubating thesupport with a solution containing about 4 μg/ml BSA and about 10 μg/mlAGP.
 7. The support of claim 1 wherein the matrix layer is obtained by aprocess which comprises incubating the support with a solutioncontaining about 6 μg/ml HSA.
 8. The support of claim 4 wherein thematrix layer is obtained by a process which comprises incubating thesupport with a solution containing about 6 μg/ml HSA and about 10 μg/mlAGP.
 9. The support of claim 1 wherein a detecting portion of thesurface further contains an effective amount of surface antitarget. 10.The support of claim 1 wherein the surface antitarget is the semenprotein p30.
 11. The support of claim 1 wherein the surface antitargetis BSA.
 12. A method for preparing a solid support useful in animmunoassay, which comprises applying a matrix layer to said support,wherein said matrix layer contains an effective amount of both a noisereduction component and a noise balancing component, wherein said noisereduction and noise balancing components are different from each otherand different from any surface anti-target used in the immunoassay. 13.The method of claim 12 wherein the matrix layer is applied as a solutioncontaining an effective amount of a noise reduction component and anoise balancing component.
 14. The method of claim 13 wherein the noisereduction component is a macromolecule having a pI below 6 and the noisebalancing component is a macromolecule having a pI higher than that ofsaid noise reduction component.
 15. The method of claim 13 wherein thenoise reduction component is selected from the group consisting of apolyamino acid, protein, glycoprotein, polysaccharide, glycolipid, andamphipathic macromolecules and wherein the noise-balancing component isselected from the group consisting of proteins, polypeptides, andamphiphatic macromolecules.
 16. The method of claim 13 wherein the noisereduction component is α-acid glycoprotein (AGP) and the noise balancingcomponent is selected from the group consisting of human and bovineserum albumin (HSA and BSA).
 17. The method of claim 13 wherein thematrix layer is obtained by a process which comprises incubating thesupport with a solution containing about 4 μg/ml BSA.
 18. The method ofclaim 13 wherein the matrix layer is obtained by a process whichcomprises incubating the support with a solution containing about 4μg/ml BSA and about 10 μg/ml AGP.
 19. The method of claim 13 wherein thematrix layer is obtained by a process which comprises incubating thesupport with a solution containing about 6 μg/ml HSA.
 20. The method ofclaim 13 wherein the matrix layer is obtained by a process whichcomprises incubating the support with a solution containing about 6μg/ml HSA and about 10 μg/ml AGP.
 21. The method of claim 13 wherein thesupport is coated in control surface portions with matrix layer aloneand in test portions with matrix layer and with an effective amount ofsurface antitarget.
 22. The method of claim 21 wherein the test portionsare coated with an admixture of the surface antitarget and the matrixlayer.
 23. The method of claim 21 wherein the test portions are coatedfirst with matrix layer and subsequently with surface antitarget. 24.The method of claim 21 wherein the test portions are coated with surfaceantitarget and then with matrix layer.
 25. A method to eliminate falsepositives in solid-supported immunoassays, which method comprisesconducting said immunoassays with a protocol which includes the step ofcontacting a sample or reagent with the solid support of claim
 1. 26. Amethod of optimizing the composition of a matrix layer effective inimproving the results of a solid support immunoassay, which comprisesdetermining the matrix index for a variety of matrix layer compositionsand selecting the composition with the highest matrix index.
 27. Amethod of optimizing the composition of a matrix layer effective inimproving the results of a solid supported immunoassay which comprisesdetermining the noise balance ratio for a series of matrix compositionsand selecting the composition with the noise balance ratio closest tounity.
 28. A solid support suitable for determining the relative noisereduction capabilities of at least two macromolecules of varyingisoelectric points for the assay of a desired target, which comprises asolid support containing a series of test regions, which test regionscontain, in series, each of said candidate macromolecules of varyingisoelectric points.
 29. A method for selecting a candidate noisereduction component for a solid phase immunoassay which comprisesapplying a concentrated form of a biological sample to be assayedlacking target to the solid support of claim 28 and measuring therelative amounts of nonspecific binding in each region of the series oftest regions.
 30. A method of conducting a solid phase immunoassay whichcomprises applying a sample to be tested for target substance to solidsupport containing control surface portions and test portions whereinthecontrol surface portions contain a matrix layer comprising at least oneof an effective amount of noise reduction component and an effectiveamount of noise balancing component, and wherein the test portionscontain said matrix layer in admixture with an effective amount ofsurface antitarget; washing the support; treating the support withdetecting antitarget; washing said support, and detecting the presenceor absence of detecting antitarget on the support.
 31. The method ofclaim 30 which further includes blocking the support with a detergent orwith a detergent plus protein mixture before treating the support withsample.